Metabotropic Glutamate Receptors Type 3 and 5 Feature the “NeuroTransmitter-type” of Glioblastoma: A Bioinformatic Approach

Background Glioblastoma (GBM) represents an aggressive and common tumor of the central nervous system. The prognosis of GBM is poor, and despite a refined genetic and molecular characterization, pharmacological treatment is largely suboptimal. Objective Contribute to defining a therapeutic line in GBM targeting the mGlu3 receptor in line with the principles of precision medicine. Methods Here, we performed a computational analysis focused on the expression of type 3 and 5 metabotropic glutamate receptor subtypes (mGlu3 and mGlu5, respectively) in high- and low-grade gliomas. Results The analysis allowed the identification of a particular high-grade glioma type, characterized by a high expression level of both receptor subtypes and by other markers of excitatory and inhibitory neurotransmission. This so-called neurotransmitter-GBM (NT-GBM) also shows a distinct immunological, metabolic, and vascularization gene signature. Conclusion Our findings might lay the groundwork for a targeted therapy to be specifically applied to this putative novel type of GBM.


INTRODUCTION
Glioblastoma multiforme (GBM) accounts for 12-15% of all intracranial tumors and 60-75% of glial tumours [1].GBM has an incidence of 3-4 cases per 100,000/year, with a peak between 45 and 75 years of age and is more prevalent in males.GBM has a poor prognosis, with an average survival of about 12 months, because of the high proliferation rate and resistance to the current therapy.Glioma stem cells, which likely originate in zones of active neurogenesis of the adult brain, support tumor growth and are highly resistant to both radio-and chemotherapy [2,3].
According to the 2021 World Health Organization Classification of CNS cancers, gliomas (astrocytomas and oligodendrogliomas) are subdivided into four grades of *Address correspondence to this author at the IRCCS Neuromed, Pozzilli, Italy; E-mail: giuseppe.battaglia@neuromed.it # These authors contributed equally to this work.severity on the basis of their histologic features (mitotic index, absence or presence of nuclear atypia, neovascularization, and necrosis).GBM is a grade-IV astrocytoma characterized by high mitotic activity, nuclear atypia, cell pleomorphism, extensive neovascularization and/or necrosis [1].The morphological classification of gliomas has been integrated with the introduction of genetic markers, such as the IDH1 gene encoding the enzyme, isocitrate dehydrogenase type-1, co-deletion of chromosomes 1p-19q, and deletion of X chromosome [3][4][5].The DNA alkylating agent, temozolomide, is the gold standard drug in the treatment of GBM, but its efficacy is limited and restricted to GBM cells that do not express the resistance enzyme, O6-methylguanine-DNA methyltransferase (MGMT) [6].The identification of molecular targets, such as the epidermal growth factor and fibroblast growth factor receptors, the membrane tyrosine kinase, MET, vascular endothelial growth factor, the phosphatidylinositol-3kinase (PI3K) pathway, and cyclin-dependent kinases, paved the way to the application of precision medicine in the treatment of brain gliomas [7,8].Metabotropic glutamate (mGlu) receptors fall into this scenario.mGlu receptors are G-protein coupled receptors activated by glutamate, the major excitatory neurotransmitter in the CNS.mGlu receptors form a family of eight subtypes, subdivided into three groups on the basis of their amino acid sequence and G-protein coupling.Group I includes mGlu1 and mGlu5 receptors, which are coupled to G q/11 .Their activation stimulates the hydrolysis of phosphatidylinositol-4,5-bisphosphate, with the ensuing formation of the second messengers, inositol-1,4,5-trisphosphate (InsP 3 ) and diacylglycerol (DAG).InsP 3 releases Ca 2+ from intracellular stores, whereas DAG facilitates the activation of protein kinase C. Group-II (mGlu2 and -3) and group III (mGlu4, -6, -7, and -8) subtypes are coupled to G i/o , and their activation inhibits adenylyl cyclase activity [9,10].mGlu receptors modulate excitatory synaptic transmission and are found in all elements of the tetrapartite synapse, i.e., axon terminals, postsynaptic densities, astrocytes, and microglia (reviewed by Nicoletti et al., 2011) [11].However, mGlu receptors are also present in cancer cells, where they have been implicated in mechanisms regulating cell proliferation, differentiation, resistance to chemotherapy and oncogenic transformation [12][13][14][15][16][17].mGlu receptors have been consistently detected in glioma cells, glioma cell lines, glioma stem cells (GSCs), and bioptic specimens of human gliomas.In rat, C6 glioma cell lines, mGlu receptor ligands displace specifically bound [3H]glutamate with a rank order of affinity that was consistent with the presence of either mGlu1 or mGlu5 receptors [18], and the transcript encoding the mGlu5 receptor was detected in human grade II astrocytoma specimens [19].mGlu3 and/or mGlu5 receptors were detected in human GBM cell lines [20][21][22], whe re the two receptors differentially regulate the expression of the glial glutamate transporters, GLAST and GLT-1 [21].Two studies have shown that glioma cells express mGlu1 receptors and depend on mGlu1 receptor signaling for their viability [23,24].Interestingly, mGlu1 receptors are ectopically expressed in melanomas and support tumor spreading in mice [25].The role of mGu5 receptors in the biology of glioma cells is largely unknown.The evidence that mGlu5 receptor blockade facilitates hypoxic glioma cell death [26] encourages using brain permeant mGlu5 receptor antagonists in experimental animal models of malignant gliomas.The mGlu3 receptor is the most extensively studied mGlu receptor subtype in glioma cells and is a promising target for therapeutic intervention.The mGlu3 receptor displays a high affinity for glutamate [27] and, therefore, can be potently activated by the glutamate released from glioma cells via the glutamate:cysteine antiporter or spread out from the surrounding synapses.The evidence that mGlu3 receptor blockade reduced glioma cell proliferation and restrained tumor growth in mice [22] laid the groundwork for the study of mGlu3 receptors in GSCs.Ciceroni et al. (2008) [28] were the first to show that GSCs express mGu3 receptors and that receptor activation sustains the undifferentiated state of GSCs by negatively modulating the action of bone morphogenetic proteins.Pharmacological blockade of mGlu3 receptors with the orthosteric antagonist, LY341495, induced GSC differentiation into astrocytes and 3-month treatment with LY341495 reduced the size of gliomas generated by intracerebral infusion of GSCs in nude mice.In a subsequent study, the same group was able to demonstrate that endoge-nous activation of mGlu3 receptors increased the resistance of GCSs to temozolomide by enhancing MGMT expression through a signaling pathway that involved PI3K and nuclear factor-κB (NFκB) [29].Interestingly, mGlu3 receptor antagonists enhanced temozolomide toxicity in cultured GSCs and synergized with temozolomide in reducing the size and spreading of brain tumors originating from GSCs in mice [29].All these findings have been largely confirmed by most recent studies [30][31][32], which, together, support the use of mGlu3 receptor antagonists in the treatment of malignant gliomas.The mGlu8 receptor may act as a counterpart of the mGlu3 receptor because glioma cell clones with downregulated mGlu8 receptors showed a higher proliferation rate and increased resistance to chemotherapy [33].
One of the limitations in the development of new therapeutic targets is the heterogeneity of human gliomas, which may generate a high variability in drug response.Interestingly, patients with surgically removed GBM treated with temozolomide showed a longer overall survival if the resected tumor had low levels of mGlu3 transcript, and the methylation state of the MGMT gene promoter influenced survival only in patients with low mGlu3 receptor mRNA in the tumor [29].Thus, treatment with mGlu3 receptor antagonists or negative allosteric modulators (NAMs) is expected to be effective in patients with high expression levels of mGlu3 receptors in GBM, who are otherwise resistant to adjuvant therapy with temozolomide.It is important to identify a tumor signature and a possible tumor subtype that predicts the expression levels of mGlu3 receptors in malignant gliomas.We have used a bioinformatics approach extending the analysis to the mGlu5 receptors because mGlu3 and mGlu5 receptors functionally interact in brain tissue [34] and are both expressed in glioma cells.

MATERIALS AND METHODS
To examine the expression of mGlu3 and mGlu5 receptors in GBM, available datasets (GSE15824, GSE23806, GSE36245 and GSE53733) were obtained from Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/).GSE15824 included genes from 30 brain tumor samples.GSE23806 included a large panel of human GBM stem-like cell lines corresponding to primary tumors and conventional glioma cell lines, from which we selected 12 primary GBM tumor samples.GSE36245 included 46 GBM samples from patients of different ages.GSE53733 included genes from 70 GBM patients of the German Glioma Network.
Data were analyzed with R studio (RStudio: Integrated Development for R. RStudio, PBC, Boston, MA) using the following packages: "affy," "impute," "tidyverse," "cluster," "factoextra" and "Limma" [41][42][43][44][45][46].Designed probes were analyzed using the "mas5calls" function, which performs a Wilcoxon signed rank-based gene expression presence/absence detection algorithm; only probes with at least 75% of samples defined as present were analyzed (Present or "P" represents a call of present, assuming that data do not represent an absent transcript).Among different probes that identify the same gene, we selected the one with higher variance.
The expression measures were obtained with RMA, a function that converts an AffyBatch into an ExpressionSet using the robust multi-array average (RMA) expression measure.
We only analyzed samples with "P-value" for both mGlu3 and mGlu5 receptors.
In order to investigate the differential expression of cluster of genes associated with immune response, hypoxia, vascular response, and cell proliferation, we have applied the same gene panel used by Reifenberger in 2014 for the molecular characterization of long-term survivors of GBM through a genomic and transcriptomic analysis [47].
In order to obtain the missing data, we performed the knearest neighbor algorithm (KNN), a machine learning method that allows to forecast of missing values after a training phase of the algorithm (consists of storing the feature vectors and class labels of the training samples).The KNN was performed with the impute.knnfunction, which imputes missing expression data using the nearest averaging neighbor.The k value (number of neighbors to be used in the imputation) was established as the square root of the number of samples.
To evaluate the GBM hierarchical clustering based on mGlu3 and mGlu5 receptor expression, we determined the optimal number of clusters with the average Silhouette Method; then, starting from the mGlu3 and mGlu5 receptor expression matrix, we computed a dissimilarity matrix and performed an agglomerative hierarchical clustering.
We used a Shapiro-Wilk test as a normality test on the expression data matrix; based on the normality parameter, correlations between genes were obtained by Pearson and Spearman's rank correlation analysis for parametric and nonparametric data, respectively.Differences in gene expression among groups were obtained using unpaired two-tailed Student's t-test with Welch's correction (parametric data); non-parametric data were analyzed with the Mann-Whitney test.
Differentially expressed genes and their significance were identified by analyzing the datasets with the R-package "Limma."In order to avoid false positive data, we have confirmed the data using the "mas5calls" function and analyzing only probes with a present call.We subsequently performed a test with Welch's correction when the data's distribution was normal; Mann Whitney test was used in non-normal data.Statistical analysis was performed with GraphPad Prism 9.4.1 (GraphPad Software, San Diego, CA, USA) Microsoft Excel 16. 16.3.For comparisons between low-grade glioma and GMB tissues, the expression dataset was obtained by the TCGA GBMLGG dataset (515 low-grade glioma samples and 152 GBM samples) [48] and the Rembrandt dataset (225 lowgrade gliomas samples and 219 GBM samples) [49].Differential expression was assessed using the t-test with Welch's correction when the data's distribution was normal; Mann Whitney test was used in non-normal data.
In order to validate the results on differentially expressed genes and differential expression of clusters of genes associated with the different signatures, we repeated our analysis using the TCGA GBM dataset (528 GBM samples) as described above [50].The TCGA database can be downloaded from the GlioVis data portal (http://gliovis.bio-73info.cnio.es/)[51].
For the correlation between mGlu3 and mGlu5 expression and clinical parameters, we used Chi-square analysis.Comparison of Survival Curves was effectuated using the "Log-rank (Mantel-Cox) test."The results shown here are in whole or part based upon data generated by the TCGA Research Network: https://www.cancer.gov/tcga.

Hierarchical Cluster Analysis Identified a GBM Group with High Expression of mGlu3 and mGlu5 Receptors
We first examined the expression levels of the genes encoding the mGlu3 and mGlu5 receptors (GRM3 and GRM5, respectively) in GBM samples from 83 patients and in samples of lower-grade gliomas from 15 patients; the overall analysis showed a greater expression of both mGlu3 and mGlu5 receptors in GBM with respect to lower grade gliomas (p = 0.0018 and p = 0.0221 respectively).
We performed a hierarchical cluster analysis of GBM based on mGlu3 and mGlu5 receptor expression; "two" was the optimal number of clusters determined with the Silhouette method (Fig. 1a).We then performed an agglomerative hierarchical clustering and analyzed the two GBM subgroups (Fig. 1b).As shown in Fig. (2), the first subgroup, named "neurotransmitter (NT)-type," showed a higher expression of mGlu3 and mGlu5 receptors (p < 0.0001) with respect to the second subgroup (the Not Otherwise Specified or "NOS" subgroup).
Afterward, we made an individual comparison of the two GBM subgroups with low-grade gliomas, finding that only the NT subgroup showed a higher expression of mGlu3 and mGlu5 receptors (Fig. 2).
We used the same approach to cluster the GBM samples from the TCGA and Rembrandt datasets (737 low-grade gliomas and 371 GBM samples).The hierarchical cluster analysis identified two different subgroups in GBM samples, similar to the previous research.These two identified groups differ in the expression levels of both mGlu3 and mGlu5 receptors, where the "NT-type" expresses significantly high levels of the receptors as compared to the "NOS-type" (p < 0.0001) (Fig. 3).The different expression levels of GRM3 and GRM5 in "NT-type" and "NOS-type" was confirmed; however, the difference between low-grade gliomas and GMB was variable and dataset-dependent.
Analyzing microarray datasets, no difference in the IDH1 or H3F3a mutational status was found between the two GBM subgroups, but the value of this analysis is limited by the low number of samples used for IDH1 and H3F3a analysis.

Fig. (1). (a) the optimal number of clusters determined with the Silhouette method; (b) Agglomerative hierarchical clustering of 83 GBM samples identify two main groups of GBM: the NT-GBM in red and the NOS-GBM in green. (A higher resolution/colour version of this figure is available in the electronic copy of the article).
Repeating analysis in the TGCA dataset, no difference in MGMT methylation status, IDH1 mutational status, CpG island methylator phenotype, gender and age were found between the two GBM subgroups, but the analysis is limited by the low number of samples with a strict molecular characterization.

The NT-type Group Displays Different Immunity, Vascular and Hypoxic Signatures with Respect to the NOS Group
We attempted to identify specific signatures of GBM with a high expression of mGlu3 and mGlu5 receptors, examining a cluster of genes associated with immune response, hypoxia, vascular response/extracellular matrix (ECM), and cell proliferation.Bioptic samples containing the NT-type GBM subgroup showed:

The NT Group is Characterized by a "Neurotransmitter" Signature and Displays Several Differential Expressed Genes
We extended the analysis to individual genes that are differentially expressed in the two subgroups of GBM and associated with a high or low expression of mGlu3 and mGlu5 receptors.The NT subgroups showed a greater expression of the following genes related to glutamatergic or GABAergic neurotransmission: GABRB2 and GABRB3, encoding the β 2 and β 3 subunits of GABA A receptors (p = 0.0002 and p < 0.0001, respectively); GRIA2, encoding the GluA 2 subunit of AMPA receptors (p = 0.0021); and GRID1, encoding the δ 1 subunit of ionotropic glutamate receptors subunit (p = 0.0007).This supports the neurotransmitter phenotype of the NT GBM subgroup.
Finally, we analyzed the correlations between mGlu3 and mGlu5 receptor expression and genes differentially expressed in the two GBM subgroups, finding that most of these genes showed a high correlation with both mGlu3 and mGlu5 receptors (Table 3).

The NT-type and the NOS-type do not Differ in Terms of Overall Survival
Finally, we tried to clarify whether the different expressions of mGlu3 and mGlu5 receptors in GBM could influence overall survival (OS) and progression-free survival (PFS).Among datasets, the only one that provides accurate information about the OS is the TGCA dataset.The analysis did not reveal significant differences in terms of OS between "NT-group" and "NOS-group" (Fig. 5a).However, analyzing OS in the different GBM subtypes, we could observe a trend of worst prognosis of "NT-type" in proneural subtypes rather than classic or mesenchymal GBM (Fig. 5b).More studies are required in order to understand these data, which are consistent with those demonstrated by Ciceroni et al. [29].
Accurate information about the PFS was not provided by any of the datasets used for our research.

DISCUSSION
Our computational analysis suggests that mGlu3 and mGlu5 receptors represent potential molecular markers of GBM.This is in line with the evidence that levels of the transcript encoding the mGlu3 receptors in tumor specimens were inversely related to the survival of patients with grade GBM undergoing surgery and adjuvant treatment with temozolomide [29].We focused on mGlu3 and mGlu5 receptors because these receptors functionally interact in brain tissue, with mGlu3 receptors boosting mGlu5 receptor signaling [34].An attractive hypothesis is that this form of receptor cross-talk also occurs in glioma cells and supports cell proliferation and chemoresistance.
As underscored in the Introduction, mGlu5 receptors are coupled to G q/11 , and their activation leads to the formation of InsP 3 and DAG, with ensuing intracellular Ca 2+ release and PKC activation (reviewed by Nicoletti et al., 2011) [11].These signaling molecules might have a profound impact on basic mechanisms of cancer cell biology, such as proliferation and survival.It will be interesting to examine whether the functional cross-talk between mGlu3 and mGlu5 receptors also exists in GBM cells or GSCs.
Interestingly, mGlu3 and mGlu5 receptors appeared to be highly expressed by a subgroup of GBM characterized by the expression of established markers of glutamatergic and GA-BAergic neurotransmission, denominated "NT-type" GBM.Only the "NT-type" GMB showed an enhanced mGlu3 and mGlu5 receptor expression with respect to low-grade gliomas, and, therefore, the two receptors cannot be considered as biochemical markers of GBM with respect to other types of gliomas but may facilitate the identification of a specific GBM subgroup.The proposed "NT-type" could not be differentiated on the basis of the mutational state of IDH1 and H3F3a, but the data were biased by the low sample size.It will be interesting to examine the association of mGlu3 and mGlu5 receptors with genetic markers that predict the evolution of low-grade gliomas into GBM, such as chromosome X deletion [1,8].
Besides genes related to glutamatergic and GABAergic transmission, genes related to innate or adaptive immunity were differentially expressed by the "NT-type" GBM.This suggests that the "NT-GBM" has a different immune signature concerning other gliomas.Several genes typically expressed in macrophages, microglia, and lymphocytes or associated with macrophage activation were differentially ex- pressed in "NT-GBM '' compared with other gliomas.It is possible that owing to the immune-related phenotype, "NT-GBM" exhibits a lower level of immune infiltration and, therefore, a reduced response to immunotherapeutic treatments.This attractive hypothesis warrants further investigation.We have also found that a cluster of genes implicated in hypoxia and angiogenesis was lesser expressed in "NT-GBM" than in "NOS-GBM".This might result in a less vascularized microenvironment, which might limit cancer cell survival.A cluster of genes related to the extracellular matrix also showed a lower expression in "NT-GBM".As opposed to what is observed in peripheral tissues, the ECM in CNS lacks collagen, fibrinogen and laminin and is predominantly formed by proteoglycans, hyaluronic acid and tenascin C (reviewed by Vollmann-Zwerenz et al., 2020) [52].It has been reported that the siRNA-induced downregulation of the chondroitin sulphate proteoglycan, versican V1, reduced the migration of high-grade glioma cells [53].Therefore, the lower expression of ECM-related genes might restrain the migration capacity of "NT-GBM cells".
Using samples from the TGCA dataset, a proliferative signature seems to characterize the "NT-GBM" versus the "NOS-GBM."This difference probably depends on the increase in sample size.
"NT-GBM" was also characterized by a differential expression of genes involved in lipid metabolism, such as SCD1.SCD1, which is heterogeneously expressed in gliomas, protects cancer cells against lipotoxicity by promoting the formation of monounsaturated fatty acids, and its inhibition increases apoptotic cell death and cell vulnerability to chemotherapy [54].Interestingly, IDH1 mutations cause changes in the expression of SCD1 in glioma cells [55][56][57][58].Other genes differentially expressed by "NT-GBM" include fatty acid 2-hydroxylase and genes encoding proteins that are involved in myelin formation.Although the two subgroups do not differ in terms of OS, the metabolic signature that we have identified in "NT-GBM" may pave the way to targeted therapy for this glioma subtype and consequently affect both OS and PFS.

CONCLUSION
In conclusion, our computational analyses allowed the identification of a putative novel GBM-type expressing high levels of mGlu3 and mGlu5 receptors, as well as other genes related to glutamatergic and GABAergic neurotransmission.Although the impact of glutamate and GABA receptors on the proliferation, survival, and migration of "NT-GBM" cells remains to be explored, we speculated that a list of some of these receptors might be targeted for therapeutic intervention.Previous studies have demonstrated that the expression of the gene encoding the mGlu3 receptor positively correlates with the severity of high-grade gliomas in humans, and pharmacological blockade of mGlu3 receptors restrains glioma growth has enhanced glioma cells vulnerability to temozolomide in preclinical models [28,29].Despite the limitations of our pure bioinformatics approach, our findings may encourage the development of selective mGlu3 receptor antagonists or negative allosteric modulators for the treatment of "NT-GBM" in conformity with the principles of precision medicine.

HUMAN AND ANIMAL RIGHTS
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CONSENT FOR PUBLICATION
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Fig. ( 3
Fig. (3).(a) the NT-group displays a significantly higher expression of both mGlu3 and mGlu5 receptors than the NOS-group in the TGCA LGGGBM dataset (****p < 0.0001); (b) the NT-group displays a significantly higher expression of both mGlu3 and mGlu5 receptors than NOS-group in Rembrandt dataset (p < 0.0001).(A higher resolution/colour version of this figure is available in the electronic copy of the article).

Fig. ( 4 )
Fig. (4).NT type (NTT) is observed more frequently in the proneural GBM subtype rather than classical and mesenchymal ones.(A higher resolution/colour version of this figure is available in the electronic copy of the article).

Fig. ( 5
Fig. (5).(a) No difference in survival between NT-group and NOS-group (p = 0,6917); (b) NT-group showed the worst prognosis in the proneural subgroup but not in classic and mesenchymal subtypes.(A higher resolution/colour version of this figure is available in the electronic copy of the article).

Table 1a . Immune signature -Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.

Table 1b . Hypoxia signature -Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.

Table 1c . Extracellular matrix signature -Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.

Table 1d . Proliferation signature -Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.

Table 2a . Immune signature -Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.

Table 2b . Hypoxia signature -Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.

Table 2c . Extracellular matrix signature -Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.

Table 2d . Proliferation signature -Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.

Table 3 . Positive values indicate a higher expression in the NOS group.
Note: Negative values indicate a higher expression in the NTT group.
Note: Negative values indicate a higher expression in the NTT group.